This archive contains answers to questions sent to Unidata support through mid-2025. Note that the archive is no longer being updated. We provide the archive for reference; many of the answers presented here remain technically correct, even if somewhat outdated. For the most up-to-date information on the use of NSF Unidata software and data services, please consult the Software Documentation first.
Hi Marc, re: how to use IR imagery to determine cloud base/top heights > Going back to this statement, would I be able from, Mcidas V, determine the > cloud base/top > height once I determine the temperature of the layer of clouds in the image > by using a > profile of temperatures? I was thinking of this just in case I have trouble > from my friend's > analyses. I would say that you could "estimate" the cloud top height (or pressure) using the observed infrared temperature if you know the vertical profile of temperatures in the atmosphere near the cloud you are interested in. I say estimate since the energy seen from the satellite is not from a specific part of the cloud. Rather, it is the result of radiation at all levels in the field of view. Knowing the weighting function for the wavelength bands you have imagery for will help define where the majority of the energy is coming from. re: out of curiosity, how does that algorithm determine cloud top pressure from a single band? > This is the information of their algorithm available on their website: > > Visible Infrared Solar-Infrared Split Window Technique (VISST) > > + Algorithm > - Daytime > - 0.65, 3.9, 10.8, 12.0 µm channels > - Utilizes parameterization of theoretical radiance calculations for 7 water > and 9 ice crystal size distributions > - Retrieves cloud optical properties by matching calculations to observations > > + Required Inputs > - Atmospheric profiles from model runs or in situ measurements > - Surface characterization from IGBP 10 minute map > - Uses CERES cloud mask algorithm > - Clear sky reflectances from CERES > - Narrowband to Broadband flux conversion functions > - Satellite data (GOES 8-10, 12; 4-km: AVHRR, 1 or 4-km) > > + Products > - Pixel-level and gridded cloud properties (t, Re, LWP, IWP, Phase, etc) > > + Domains > - ARM SGP, ARM TWP, CONUS East and West Very good. This synopsizes in a much better way what I was trying to say -- one needs a LOT more than just one satellite image band to deduce cloud parameters like base/top heights/pressures, etc. Cheers, Tom **************************************************************************** Unidata User Support UCAR Unidata Program (303) 497-8642 P.O. Box 3000 address@hidden Boulder, CO 80307 ---------------------------------------------------------------------------- Unidata HomePage http://www.unidata.ucar.edu **************************************************************************** Ticket Details =================== Ticket ID: OXG-395498 Department: Support McIDAS Priority: Normal Status: Closed